Physical AI Lab is a complete research and education platform designed to support advanced projects in Robotics, Applied AI, and Physical AI. The solution enables end-to-end research workflows—from algorithm development and training to deployment, testing, and validation on real robotic hardware.

At the core of the laboratory is QArm Research, a six-degree-of-freedom robotic manipulator developed specifically for academic research. Combined with the QBrain NVIDIA-based edge computing unit, the QLabs digital twin, the Haptic Robot for teleoperation and imitation learning, and a Force/Torque Transducer, it provides a comprehensive platform for developing and evaluating intelligent robotic systems.

The laboratory includes a rich collection of ready-to-use applications and examples covering classical robotics, motion planning, perception, control, machine learning, and Physical AI. This allows researchers to focus on developing algorithms and conducting experiments rather than spending valuable time integrating hardware and software components.

The platform supports widely adopted research tools and frameworks, including ROS 2, NVIDIA Isaac, Python, C++, MATLAB/Simulink, and QUARC, making it easy to transition applications between simulation and physical robotic platforms.

Its modular architecture allows the laboratory to be expanded with QBot Platforms, a Ground Control Station (GCS), and additional communication infrastructure, creating a scalable environment for research in autonomous systems, multi-robot collaboration, and next-generation Physical AI.